Speckle noise (also called “speckle” in the following) is a granular noise that inherently exists in and degrades the quality of images obtained by active imaging devices, such as active radars, and synthetic aperture radars (SARs). Speckle noise in conventional radar results from random fluctuations in the return signal from an object that is no bigger than a single image-processing element. It increases the mean grey level of a local area.
Various techniques have been proposed to reduce the effect of speckle for illumination systems such as laser projectors, but these techniques concentrate on removing the phase coherence of the transmitted signal, which help to decrease the speckle on the final image. Such techniques however cannot be used for an active imaging device, since it is important that the transmitted signal in an active imaging device maintains its phase coherence.
The use of multiple frequency techniques to reduce the effects of speckle in an active imaging device has been proposed in I. Jaeger et al, “Comparison of speckle reduction diversity tools for active millimeter-wave imaging”, Journal of the Optical Society of America, Vol. 25, No. 7, July 2008. This paper describes (in section 3) the use of more than one frequency to reduce the effects of speckle. In particular, it explains that when an object is illuminated with two frequencies, the amount of speckle noise can be reduced as the difference between these frequencies is increased. It also further indicates that to obtain a desired speckle reduction for a given object, the difference frequency between these two frequencies may have to be adaptively changed, in accordance with the optical properties of the object, which undesirably may need a large bandwidth.
The use of the properties of different image feature/structures for selecting how to best filter the final image to reduce the effects of speckle in an active imaging device is described in Zengguo et al, “Research and Improving on Speckle MMSE Filter Based on Adaptive Windowing and Structure Detection”, IEEE International Conference on Vehicular Electronics and Safety 2005, pp. 251-256. This paper describes a technique to reduce speckle for an image in which different image features are first classified into heterogeneous or homogenous areas. Features in the heterogeneous areas are then further identified and for each type of feature (line, edge, point) different types of filtering are used to reduce the speckle noise.